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GNSS反演资料在GRAPES_Meso三维变分中的应用

王金成 龚建东 邓莲堂

王金成, 龚建东, 邓莲堂. GNSS反演资料在GRAPES_Meso三维变分中的应用. 应用气象学报, 2014, 25(6): 654-668..
引用本文: 王金成, 龚建东, 邓莲堂. GNSS反演资料在GRAPES_Meso三维变分中的应用. 应用气象学报, 2014, 25(6): 654-668.
Wang Jincheng, Gong Jiandong, Deng Liantang. Operational assimilation of data retrieved by GNSS observations into GRAPES_MESO 3DVar system. J Appl Meteor Sci, 2014, 25(6): 654-668.
Citation: Wang Jincheng, Gong Jiandong, Deng Liantang. Operational assimilation of data retrieved by GNSS observations into GRAPES_MESO 3DVar system. J Appl Meteor Sci, 2014, 25(6): 654-668.

GNSS反演资料在GRAPES_Meso三维变分中的应用

资助项目: 

国家国际科技合作专项 2011DFG23210

公益性行业 (气象) 科研专项 GYHY201406011

详细信息
    通信作者:

    王金成, email: wangjc@cma.gov.cn

Operational Assimilation of Data Retrieved by GNSS Observations into GRAPES_Meso 3DVar System

  • 摘要: 为了进一步提高GRAPES_Meso的分析和预报效果,该文在GRAPES_Meso三维变分同化系统中建立了同化GNSS/RO反演的大气资料的观测算子,实现了对GNSS/RO反演的大气资料的同化应用,并通过2013年7月1个月的同化和预报试验分析了GNSS/RO反演大气资料对GRAPES_Meso模式系统分析和预报的影响。结果表明:增加了GNSS/RO反演大气资料的同化后,GRAPES_Meso位势高度场的分析误差明显减小,平均分析误差减小约8%,预报误差略有减小,平均预报误差减小约1%;湿度场的分析误差和预报误差变化不明显,常规观测资料稀少的青藏高原地区的降水预报技巧有所提高,小雨到大雨的ETS (equitable threat score) 评分提高约0.01,对全国及其他分区的降水预报技巧总体上有正效果。
  • 图  1  GNSS/RO反演的气压和相对湿度的观测误差

    Fig. 1  The observation error of pressure and relative humidity retrieved by GNSS/RO data

    图  2  2013年7月12日00:00同化GNSS/RO反演的大气气压和湿度的目标函数梯度范数和目标函数的收敛性

    Fig. 2  Variations of the gradient norm and the cost-function for background and observation part with the iteration number for assimilating the GNSS/RO retrieved pressure and relative humidity at 0000 UTC 12 July 2013

    图  3  2013年7月1日00:00—2013年7月31日18:00业务上接收的6 h同化时间窗的GRAPES_Meso模拟区域内GNSS/RO资料廓线数量

    (a) 弯角,(b) 折射率,(c) 反演的大气廓线

    Fig. 3  Number of profiles of bending angle (a), refractivity (b), retrieved atmosphere pressure, temperature and humidity (c) for [-3 h, +3 h) observation window located in GRAPES_Meso simulated domain from 0000 UTC 1 July 2013 to 1800 UTC 31 July 2013

    图  4  2013年7月00:00, 12:00分析时刻GNSS/RO反演的气压及相对湿度标准差

    (a) 反演的气压与背景场偏差的标准差,(b) 反演的气压与分析场偏差的标准差,(c) 反演的相对湿度与背景场偏差的标准差,(d) 反演的相对湿度与分析场偏差的标准差

    Fig. 4  The standard deviation of retrieved pressure and relative humidity from GNSS/RO at analysis time of 0000 UTC and 1200 UTC in July 2013

    (a) the standard deviation of difference between retrieved pressure and the background, (b) the standard deviation of difference between retrieved pressure and the analysis, (c) the standard deviation of difference between retrieved relative humidity and the background, (d) the standard deviation of difference between retrived relative humidity and the analysis

    图  5  图 4,但为06:00, 18:00分析时刻

    Fig. 5  The same as in Fig. 4, but for analysis time of 0600 UTC and 1800 UTC

    图  6  2013年7月00:00, 12:00分析时刻试验OPER及试验GNSS的分析误差

    (a) 位势高度分析误差, (b) 比湿分析误差, (c) 位势高度月平均分析误差, (d) 比湿月平均分析误差 (图 6a, 6b中彩色阴影表示试验OPER分析误差,等值线表示试验GNSS与试验OPER分析误差的偏差,网格填充区域表示试验GNSS的分析误差大于试验OPER)

    Fig. 6  Variations of the analysis error for OPER and GNSS for analysis time of 0000 UTC and 1200 UTC in July 2013

    (a) analysis error of geopotential height, (b) analysis error of specific humidity, (c) monthly mean analysis error of geopotential height, (d) monthly mean analysis error of specific humidity (in Fig. 6a and Fig. 6b, the shaded denotes the analysis error of experiment OPER, the contour denotes the analysis error difference of GNSS to OPER, the net denotes the error of GNSS lager than that of OPER)

    图  7  图 6,但为06:00, 18:00分析时刻

    Fig. 7  The same as in Fig. 6, but for analysis time of 0600 UTC and 1800 UTC

    图  8  2013年7月00:00, 12:00分析时刻位势高度场24 h和48 h预报误差

    (a) 位势高度场24 h预报误差, (b) 位势高度场48 h预报误差, (c) 位势高度场月平均24 h预报误差, (d) 位势高度场月平均48 h预报误差 (图 8a, 8b中,阴影表示试验OPER的位势高度的预报误差,等值线表示试验GNSS与OPER预报误差偏差,网格表示试验GNSS预报误差大于试验OPER)

    Fig. 8  Variations of 24-h and 48-h forecast errors of geopotential height for analysis time of 0000 UTC and 1200 UTC in July 2013

    (a)24-h forecast error, (b)48-h forecast error, (c) monthly mean 24-h forecast error, (d) monthly mean 48-h forecast error (in Fig. 8a and Fig. 8b, the shaded denotes the error of OPER, the contour denotes the forecast error difference of GNSS to OPER, the net denotes the forecast error of GNSS larger than that of OPER)

    图  9  2013年7月00:00, 12:00分析时刻试验GNSS降水预报0~24 h预报 (a),12~36 h预报 (b) 和24~48 h预报 (c) 的24 h累积降水ETS评分月平均值与试验OPER偏差

    Fig. 9  Differences of ETS values of 0-24 h (a), 12-36 h (b) and 24-48 h (c) accumulated rainfall of GNSS to OPER for analysis time of 0000 UTC and 1200 UTC in July 2013

    图  10  2013年7月06:00,18:00分析时刻试验GNSS 6~30 h预报 (a),18~42 h预报 (b)24 h累积降水ETS评分月平均值与试验OPER偏差

    Fig. 10  Differences of ETS values of 6-30 h (a), 18-42 h (b) accumulated rainfall of GNSS to OPER for analysis time of 0600 UTC and 1800 UTC in July 2013

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  • 收稿日期:  2014-05-13
  • 修回日期:  2014-09-17
  • 刊出日期:  2014-11-30

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